Deep Learning Techniques for Biomedical and Health Informatics (Studies in Big Data)
Sold by Lucky's Textbooks, Dallas, TX, U.S.A.
AbeBooks Seller since 22 July 2022
New - Soft cover
Condition: New
Quantity: Over 20 available
Add to basketSold by Lucky's Textbooks, Dallas, TX, U.S.A.
AbeBooks Seller since 22 July 2022
Condition: New
Quantity: Over 20 available
Add to basketThis book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model.
This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health.
It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.
This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model.
This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health.
It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.
"About this title" may belong to another edition of this title.
We guarantee the condition of every book as it's described on the AbeBooks web
sites. Please note that used items may not include access codes or cards, CD's
or other accessories, regardless of what is stated in item title. If you need to
guarantee that these items are included, please purchase a brand new copy.
All requests for refunds and/or returns will be processed in accordance with
AbeBooks policies. If you're dissatisfied with your purchase (Incorrect Book/Not
as Described/Damaged) or if ...
Books ordered via expedited shipping should arrive between 2 and 7 business days after shipment confirmation. Books ordered via standard shipping should arrive between 4 and 14 business days after shipment confirmation.